Plotly for Interactive Visualizations

Introduction

Plotly creates interactive, publication-quality graphs. It's ideal for dashboards and web applications where interactivity is essential.

Why Plotly?

• Interactive: Zoom, pan, hover tooltips
• Web-ready: Works with Dash, Streamlit
• Many chart types: 3D, maps, scientific charts

Basic Plotly

import plotly.express as px
import plotly.graph_objects as go
import pandas as pd

df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [10, 20, 15, 25, 30],
    'category': ['A', 'B', 'A', 'B', 'A']
})

Express Plots

# Scatter plot
fig = px.scatter(df, x='x', y='y', color='category')
fig.show()

# Line plot
fig = px.line(df, x='x', y='y')

# Bar chart
fig = px.bar(df, x='category', y='y')

# Box plot
fig = px.box(df, x='category', y='y')

# Violin plot
fig = px.violin(df, x='category', y='y')

Interactive Features

# Add hover data
fig = px.scatter(df, x='x', y='y', 
                 hover_data=['category'],
                 title='Interactive Plot')

# Facet plots
fig = px.scatter(df, x='x', y='y', 
                 facet_col='category')

# Animation
fig = px.scatter(df, x='x', y='y', 
                 animation_frame='category')

Graph Objects

# Create custom figure
fig = go.Figure()

# Add traces
fig.add_trace(go.Scatter(x=[1,2,3], y=[1,2,3], 
                        mode='lines+markers',
                        name='Line 1'))

fig.add_trace(go.Bar(x=[1,2,3], y=[3,2,1]))

# Update layout
fig.update_layout(title='Custom Figure',
                  xaxis_title='X Axis',
                  yaxis_title='Y Axis',
                  template='plotly_dark')

3D Plots

import numpy as np

# 3D scatter
fig = px.scatter_3d(df, x='x', y='y', z='category')

# 3D surface
x = np.linspace(-5, 5, 50)
y = np.linspace(-5, 5, 50)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))

fig = go.Figure(data=[go.Surface(z=Z, x=X, y=Y)])

Dash Integration

from dash import Dash, dcc, html
import plotly.express as px

app = Dash(__name__)

app.layout = html.Div([
    dcc.Graph(figure=fig),
    html.H1("Dashboard Title")
])

if __name__ == '__main__':
    app.run_server(debug=True)

Key Takeaways

1. Plotly enables interactive web visualizations
2. Use Express for quick plotting
3. Graph Objects offer full customization